scholarly journals Assessing the stability of Pd-exchanged sites in zeolites with the aid of a high throughput quantum chemistry workflow

2021 ◽  
Author(s):  
Hassan Aljama ◽  
Martin Head-Gordon ◽  
Alexis Bell
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Active Sites ◽  
Density Functional ◽  
Functional Materials ◽  
No Adsorption ◽  
Functional Theory ◽  
Wide Range ◽  
The Stability ◽  
Shed Light

Abstract Cation exchanged-zeolites are functional materials with a wide range of applications from catalysis to sorbents. They present a challenge for computational studies using density functional theory due to the numerous possible active sites. From Al configuration, to placement of extra framework cation(s), to potentially different oxidation states of the cation, accounting for all these possibilities is not trivial. To make the number of calculations more tractable, most studies focus on a few active sites. We attempt to go beyond these limitations by implementing a workflow for a high throughput screening, designed to systematize the problem and exhaustively search for feasible active sites. We use Pd-exchanged CHA and BEA to illustrate the approach. After conducting thousands of individual calculations, we identify the sites most favorable for the Pd cation and discuss the results in detail. The high throughput screening identifies many energetically favorable sites that are non-trivial. Lastly, we employ these results to examine NO adsorption in Pd-exchanged CHA, which is a promising passive NOx adsorbent (PNA) during the cold start of automobiles. The results shed light on critical active sites for NOx capture that were not previously studied.

SoftBV – a software tool for screening the materials genome of inorganic fast ion conductors

2019 ◽  
Vol 75 (1) ◽  
pp. 18-33 ◽  
Author(s):  
Haomin Chen ◽  
Lee Loong Wong ◽  
Stefan Adams
Keyword(s):  
Force Field ◽  
High Throughput ◽  
High Throughput Screening ◽  
Density Functional ◽  
Inorganic Compounds ◽  
Computational Cost ◽  
Lewis Base ◽  
Computational Screening ◽  
Wide Range ◽  
Dft Simulations

The identification of materials for advanced energy-storage systems is still mostly based on experimental trial and error. Increasingly, computational tools are sought to accelerate materials discovery by computational predictions. Here are introduced a set of computationally inexpensive software tools that exploit the bond-valence-based empirical force field previously developed by the authors to enable high-throughput computational screening of experimental or simulated crystal-structure models of battery materials predicting a variety of properties of technological relevance, including a structure plausibility check, surface energies, an inventory of equilibrium and interstitial sites, the topology of ion-migration paths in between those sites, the respective migration barriers and the site-specific attempt frequencies. All of these can be predicted from CIF files of structure models at a minute fraction of the computational cost of density functional theory (DFT) simulations, and with the added advantage that all the relevant pathway segments are analysed instead of arbitrarily predetermined paths. The capabilities and limitations of the approach are evaluated for a wide range of ion-conducting solids. An integrated simple kinetic Monte Carlo simulation provides rough (but less reliable) predictions of the absolute conductivity at a given temperature. The automated adaptation of the force field to the composition and charge distribution in the simulated material allows for a high transferability of the force field within a wide range of Lewis acid–Lewis base-type ionic inorganic compounds as necessary for high-throughput screening. While the transferability and precision will not reach the same levels as in DFT simulations, the fact that the computational cost is several orders of magnitude lower allows the application of the approach not only to pre-screen databases of simple structure prototypes but also to structure models of complex disordered or amorphous phases, and provides a path to expand the analysis to charge transfer across interfaces that would be difficult to cover by ab initio methods.

scholarly journals Study on Adsorption and Separation of Gas in Metal-organic Framework Materials Based on Density Functional Theory

2021 ◽  
Vol 257 ◽  
pp. 01012
Author(s):  
Du Zhehua ◽  
Lin Xin
Keyword(s):  
Density Functional Theory ◽  
High Throughput ◽  
High Throughput Screening ◽  
Density Functional ◽  
Gas Adsorption ◽  
Metal Organic Framework ◽  
Functional Theory ◽  
Main Challenge ◽  
Metal Organic ◽  
Organic Framework

This article reviews the recent progress on predicting the adsorption properties of metal-organic framework by using classical density functional theory and focused on the application of the classical density functional theory to the high-throughput screening, which is accelerated by fast Fourier Transform. Comparing to the conventional molecular simulations, the advantage of the accelerated classical density functional theory is the calculation speed, especially for simple small molecule systems, which makes the high-throughput screening on MOF materials feasible. However, it appears that there is a lack of efficient method to deal with the complicated molecules. How to construct a reasonable free energy functional of complicated fluid is the main challenge to state of art classical density functional theory. In a word, the improvement of CDFT theory and the combination of CDFT and molecular simulation are the two main ways for CDFT to predict gas adsorption in MOF.

scholarly journals A High-Throughput Study of the Electronic Structure and Physical Properties of Short-Period (GaAs)m(AlAs)n (m, n ≤ 10) Superlattices Based on Density Functional Theory Calculations

Nanomaterials ◽  
2018 ◽  
Vol 8 (9) ◽  
pp. 709 ◽  
Author(s):  
Qing-Lu Liu ◽  
Zong-Yan Zhao ◽  
Jian-Hong Yi ◽  
Zi-Yang Zhang
Keyword(s):  
Density Functional Theory ◽  
Electronic Structure ◽  
Physical Properties ◽  
Band Gap ◽  
High Throughput ◽  
Density Functional ◽  
Functional Materials ◽  
Density Functional Theory Calculations ◽  
Functional Theory ◽  
High Throughput Study

As important functional materials, the electronic structure and physical properties of (GaAs)m(AlAs)n superlattices (SLs) have been extensively studied. However, due to limitations of computational methods and computational resources, it is sometimes difficult to thoroughly understand how and why the modification of their structural parameters affects their electronic structure and physical properties. In this article, a high-throughput study based on density functional theory calculations has been carried out to obtain detailed information and to further provide the underlying intrinsic mechanisms. The band gap variations of (GaAs)m(AlAs)n superlattices have been systematically investigated and summarized. They are very consistent with the available reported experimental measurements. Furthermore, the direct-to-indirect-gap transition of (GaAs)m(AlAs)n superlattices has been predicted and explained. For certain thicknesses of the GaAs well (m), the band gap value of (GaAs)m(AlAs)n SLs exponentially increases (increasing n), while for certain thicknesses of the AlAs barrier (n), the band gap value of (GaAs)m(AlAs)n SLs exponentially decreases (increasing m). In both cases, the band gap values converge to certain values. Furthermore, owing to the energy eigenvalues at different k-points showing different variation trends, (GaAs)m(AlAs)n SLs transform from a Γ-Γ direct band gap to Γ-M indirect band gap when the AlAs barrier is thick enough. The intrinsic reason for these variations is that the contributions and positions of the electronic states of the GaAs well and the AlAs barrier change under altered thickness conditions. Moreover, we have found that the binding energy can be used as a detector to estimate the band gap value in the design of (GaAs)m(AlAs)n devices. Our findings are useful for the design of novel (GaAs)m(AlAs)n superlattices-based optoelectronic devices.

scholarly journals Computational high-throughput screening of alloy nanoclusters for electrocatalytic hydrogen evolution

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Xinnan Mao ◽  
Lu Wang ◽  
Yafeng Xu ◽  
Pengju Wang ◽  
Youyong Li ◽  
...  
Keyword(s):  
Hydrogen Evolution ◽  
High Throughput ◽  
High Throughput Screening ◽  
Active Sites ◽  
Density Functional ◽  
Screening Method ◽  
Machine Learning Techniques ◽  
Core Shell ◽  
The Core ◽  
Alloy Clusters

AbstractHere, we report a density functional theory (DFT)-based high-throughput screening method to successfully identify a type of alloy nanoclusters as the electrocatalyst for hydrogen evolution reaction (HER). Totally 7924 candidates of Cu-based alloy clusters of Cu55-nMn (M = Co, Ni, Ru, and Rh) are optimized and evaluated to screening for the promising catalysts. By comparing different structural patterns, Cu-based alloy clusters prefer the core–shell structures with the dopant metal in the core and Cu as the shell atoms. Generally speaking, the HER performance of the Cu-based nanoclusters can be significantly improved by doping transition metals, and the active sites are the bridge sites and three-fold sites on the outer-shell Cu atoms. Considering the structural stability and the electrochemical activity, core–shell CuNi alloy clusters are suggested to be the superior electrocatalyst for hydrogen evolution. A descriptor composing of surface charge is proposed to efficiently evaluate the HER activity of the alloy clusters supported by the DFT calculations and machine-learning techniques. Our screening strategy could accelerate the pace of discovery for promising HER electrocatalysts using metal alloy nanoclusters.

Theoretical Studies on the Chemical Structure of Carboxymethyl Chitosan

2010 ◽  
Vol 160-162 ◽  
pp. 1822-1827
Author(s):  
Xi Lu ◽  
Juan Qin Xue ◽  
Yu Jie Wang ◽  
Wei Bo Mao ◽  
Ming Wu ◽  
...  
Keyword(s):  
Active Sites ◽  
Density Functional ◽  
Carboxymethyl Chitosan ◽  
Water Soluble ◽  
Functional Theory ◽  
Molecular Orbit ◽  
The Density Functional Theory ◽  
Stability Order ◽  
The Stability ◽  
The One

The density functional theory (DFT) calculations explored the structural optimization and the frequency of N-carboxymethyl chitosan (N-CMCS) and O-carboxymethyl chitosan (O-CMCS). For the isomers, the calculations comparatively were performed. The charge distribution and frontier molecular orbit were analyzed by using the natural bond orbital (NBO) method. The results showed: the two rotational isomers a and b can stably exist, with the stability order a>b; N-carboxymethyl chitosan reaction active sites are concentrated in -OH and -NHCH2COOH, while O-carboxymethyl chitosan reaction active sites are concentrated in -NH2 and -CH2COOH; The water-soluble mechanism of carboxymethyl chitosan was investigated deeply, on the one hand, the presence of carboxymethyl of carboxymethyl chitosan had a tendency to ionize H+, on the other hand the carboxymethyl increased the distance and weakened the hydrogen bonds between molecules, even though Einstein shift H-bond is formed in the carboxymethyl chitosan molecules.

scholarly journals The Inhibitory Effect of Some Natural Bioactive D-Glucopyranoside Derivatives against SARS-CoV-2 Main Protease (Mpro) and Spike Protease (Spro)

2021 ◽  
Vol 16 ◽  
pp. 1-18
Author(s):  
Ajoy Kumer ◽  
Unesco Chakma ◽  
Sarkar Mohammad Abe Kawsar
Keyword(s):  
Active Sites ◽  
Density Functional ◽  
Inhibitory Effect ◽  
Binding Affinities ◽  
Ligand Interaction ◽  
Functional Theory ◽  
Main Protease ◽  
Mean Square Fluctuation ◽  
Chemical Descriptors ◽  
The Stability

Outbreak of coronavirus seems to have exacerbated across the globe, but drugs have not been discovered till now. Due to having the antiviral activity of D-glucopyranoside derivatives, this study was designed to examine as the inhibitor by in sillico study against the main protease (Mpro) and Spike protease (Spro) of SARS-CoV-2. First, these derivatives were optimised by Density Functional Theory (DFT). The observation of this study was monitored by molecular docking tools calculating the binding affinities. Afterwards, the ligand interaction with protein was accounted for selecting the how to bind of active sites of the protein. Next, the root means square deviation (RMSD) and root mean square fluctuation (RMSF) were illustrated for determining the stability of the docked complex. Finally, AMDET properties were calculated as well as the Lipisinki rule. All of the derivates showed a binding affinity more than -6.0 kcal/mol while derivatives 2, 3, and 9 were the best-bonded scoring inhibitor against Mpro and Spro. In addition, the chemical descriptors were more supportive tools as an inhibitor, and the Lipisinki rule was satisfied for maximum molecules as a drug. Besides, D-glucopyranoside derivatives may be predicted that they are non-carcinogenic and low toxic for both aquatic and non-aquatic species.

High-throughput computational material screening of the cycloalkane-based two-dimensional Dion–Jacobson halide perovskites for optoelectronics

2021 ◽  
Author(s):  
Guoqi Zhao ◽  
Jiahao Xie ◽  
Kun Zhou ◽  
Bangyu Xing ◽  
Xinjiang Wang ◽  
...  
Keyword(s):  
High Throughput ◽  
Density Functional ◽  
Perovskite Solar Cells ◽  
Two Dimensional ◽  
Photovoltaic Properties ◽  
Wide Range ◽  
Stability Issue ◽  
Halide Perovskites ◽  
The Stability ◽  
Inorganic Framework

Abstract Two-dimensional (2D) layered perovskites have emerged as potential alternates to traditional 3D analogs to solve the stability issue of perovskite solar cells. In recent years, many efforts have been spent on manipulating the interlayer organic spacing cation to improve the photovoltaic properties of Dion–Jacobson (DJ) perovskites. In this work, a serious of cycloalkane (CA) molecules were selected as the organic spacing cation in 2D DJ perovskites, which can widely manipulate the optoelectronic properties of DJ perovskites. The underlying relationship between the CA interlayer molecules and the crystal structures, thermodynamic stabilities, and electronic properties of 58 DJ perovskites has been investigated by using automatic high-throughput workflow cooperated with density-functional (DFT) calculations. We have found that these CA-based DJ perovskites are all thermodynamic stable. The sizes of the cycloalkane molecules can influence the degree of inorganic framework distortion and further tune the bandgaps with a wide range of 0.9~2.1 eV. These findings indicate the cycloalkane molecules are suitable for spacing cation in 2D DJ perovskites and provide a useful guidance in designing novel 2D DJ perovskites for optoelectronic applications.

Intrinsic Stacking Interactions of Natural and Artificial Nucleobases

2019 ◽  
Author(s):  
Drew P. Harding ◽  
Laura J. Kingsley ◽  
Glen Spraggon ◽  
Steven Wheeler
Keyword(s):  
Gas Phase ◽  
Electrostatic Interactions ◽  
Density Functional ◽  
Molecular Descriptors ◽  
Stacking Interactions ◽  
Interaction Energies ◽  
Functional Theory ◽  
Binding Partner ◽  
Heavy Atoms ◽  
Wide Range

The intrinsic (gas-phase) stacking energies of natural and artificial nucleobases were explored using density functional theory (DFT) and correlated ab initio methods. Ranking the stacking strength of natural nucleobase dimers revealed a preference in binding partner similar to that seen from experiments, namely G > C > A > T > U. Decomposition of these interaction energies using symmetry-adapted perturbation theory (SAPT) showed that these dispersion dominated interactions are modulated by electrostatics. Artificial nucleobases showed a similar stacking preference for natural nucleobases and were also modulated by electrostatic interactions. A robust predictive multivariate model was developed that quantitively predicts the maximum stacking interaction between natural and a wide range of artificial nucleobases using molecular descriptors based on computed electrostatic potentials (ESPs) and the number of heavy atoms. This model should find utility in designing artificial nucleobase analogs that exhibit stacking interactions comparable to those of natural nucleobases. Further analysis of the descriptors in this model unveil the origin of superior stacking abilities of certain nucleobases, including cytosine and guanine.

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